Instructions to use D4ve-R/wav2vec2-large-xlsr-53-german with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use D4ve-R/wav2vec2-large-xlsr-53-german with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="D4ve-R/wav2vec2-large-xlsr-53-german")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("D4ve-R/wav2vec2-large-xlsr-53-german") model = AutoModelForCTC.from_pretrained("D4ve-R/wav2vec2-large-xlsr-53-german", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6be960253e03b60d8c34ce256b9f6db1f53d0e7f7adc0256c431316cf56d17c8
- Size of remote file:
- 3.96 kB
- SHA256:
- ac03a825990e8ae6788b256b48e60d354201dd5fe003ae869e233886c92094bb
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